| 摘要 |
<p>A method of applying noise removal to an image so that the areas having the greatest variance have the least correction. First, the variance between each image pixel and its surrounding pixels is determined. Next, for the neighborhood around each pixel, a density of variance is determined. Finally the density of variance for the neighborhood around each pixel is used to correct the original pixel, the direction of correction being toward the mean value in the surrounding pixels. The result is that relatively uniform areas of the image, within which noise is most obvious, will get the most correction and areas that are textured will get the least. <IMAGE></p> |
